IDEAS home Printed from https://ideas.repec.org/a/taf/quantf/v14y2014i2p217-235.html
   My bibliography  Save this article

Longevity hedge effectiveness: a decomposition

Author

Listed:
  • Andrew J.G. Cairns
  • Kevin Dowd
  • David Blake
  • Guy D. Coughlan

Abstract

We use a case study of a pension plan wishing to hedge the longevity risk in its pension liabilities at a future date. The plan has the choice of using either a customised hedge or an index hedge, with the degree of hedge effectiveness being closely related to the correlation between the value of the hedge and the value of the pension liability. The key contribution of this paper is to show how correlation and, therefore, hedge effectiveness can be broken down into contributions from a number of distinct types of risk factors. Our decomposition of the correlation indicates that population basis risk has a significant influence on the correlation. But recalibration risk as well as the length of the recalibration window are also important, as is cohort effect uncertainty. Having accounted for recalibration risk, additional parameter uncertainty has only a marginal impact on hedge effectiveness. Finally, the inclusion of Poisson risk only starts to become significant when the smaller population falls below about 10,000 members over age 50. Our case study shows that, at least for medium and large pension plans, longevity risk can be substantially hedged using index hedges as an alternative to customised longevity hedges. As a consequence, when the hedger's population involves more than about 10,000 members over age 50, index longevity hedges (in conjunction with the other components of an ALM strategy) can provide an effective and lower cost alternative to both a full buy-out of pension liabilities or even to a strategy using customised longevity hedges.

Suggested Citation

  • Andrew J.G. Cairns & Kevin Dowd & David Blake & Guy D. Coughlan, 2014. "Longevity hedge effectiveness: a decomposition," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 217-235, February.
  • Handle: RePEc:taf:quantf:v:14:y:2014:i:2:p:217-235 DOI: 10.1080/14697688.2012.748986
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/14697688.2012.748986
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cairns, Andrew J.G. & Blake, David & Dowd, Kevin & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2011. "Mortality density forecasts: An analysis of six stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 48(3), pages 355-367, May.
    2. Jarner, Søren Fiig & Kryger, Esben Masotti, 2011. "Modelling Adult Mortality in Small Populations: The Saint Model," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 41(02), pages 377-418, November.
    3. Dowd, Kevin & Cairns, Andrew & Blake, David & Coughlan, Guy & Khalaf-Allah, Marwa, 2011. "A gravity model of mortality rates for two related populations," MPRA Paper 35738, University Library of Munich, Germany.
    4. Denuit, M. & Haberman, S. & Renshaw, A.E., 2010. "Comonotonic Approximations to Quantiles of Life Annuity Conditional Expected Present Values: Extensions to General Arima Models and Comparison with the Bootstrap," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 40(01), pages 331-349, May.
    5. Andrew J. G. Cairns & David Blake & Kevin Dowd, 2006. "A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(4), pages 687-718.
    6. Wolfgang Reichmuth & Samad Sarferaz, 2008. "Bayesian Demographic Modeling and Forecasting: An Application to U.S. Mortality," SFB 649 Discussion Papers SFB649DP2008-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Blake, D. & Cairns, A. J. G. & Dowd, K., 2006. "Living with Mortality: Longevity Bonds and Other Mortality-Linked Securities," British Actuarial Journal, Cambridge University Press, vol. 12(01), pages 153-197, March.
    8. Nan Li & Ronald Lee, 2005. "Coherent mortality forecasts for a group of populations: An extension of the lee-carter method," Demography, Springer;Population Association of America (PAA), vol. 42(3), pages 575-594, August.
    9. Czado, Claudia & Delwarde, Antoine & Denuit, Michel, 2005. "Bayesian Poisson log-bilinear mortality projections," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 260-284, June.
    10. Coughlan, Guy & Khalaf-Allah, Marwa & Ye, Yijing & Kumar, Sumit & Cairns, Andrew & Blake, David & Dowd, Kevin, 2011. "Longevity hedging 101: A framework for longevity basis risk analysis and hedge effectiveness," MPRA Paper 35743, University Library of Munich, Germany.
    11. Kogure, Atsuyuki & Kurachi, Yoshiyuki, 2010. "A Bayesian approach to pricing longevity risk based on risk-neutral predictive distributions," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 162-172, February.
    12. Olivieri, Annamaria & Pitacco, Ermanno, 2009. "Stochastic Mortality: The Impact on Target Capital," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 39(02), pages 541-563, November.
    13. Dowd, Kevin & Cairns, Andrew J.G. & Blake, David & Coughlan, Guy D. & Epstein, David & Khalaf-Allah, Marwa, 2010. "Evaluating the goodness of fit of stochastic mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 47(3), pages 255-265, December.
    14. Blake, David & Boardman, Tom & Cairns, Andrew, 2010. "Sharing longevity risk: Why governments should issue longevity bonds," MPRA Paper 34184, University Library of Munich, Germany.
    15. Carter, Lawrence R. & Lee, Ronald D., 1992. "Modeling and forecasting US sex differentials in mortality," International Journal of Forecasting, Elsevier, vol. 8(3), pages 393-411, November.
    16. Wills, Samuel & Sherris, Michael, 2010. "Securitization, structuring and pricing of longevity risk," Insurance: Mathematics and Economics, Elsevier, vol. 46(1), pages 173-185, February.
    17. Brouhns, Natacha & Denuit, Michel & Vermunt, Jeroen K., 2002. "A Poisson log-bilinear regression approach to the construction of projected lifetables," Insurance: Mathematics and Economics, Elsevier, vol. 31(3), pages 373-393, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:eee:insuma:v:76:y:2017:i:c:p:95-103 is not listed on IDEAS
    2. Kim, Joseph H.T. & Li, Johnny S.H., 2017. "Risk-neutral valuation of the non-recourse protection in reverse mortgages: A case study for Korea," Emerging Markets Review, Elsevier, vol. 30(C), pages 133-154.
    3. Andrew J.G. Cairns & Malene Kallestrup-Lamb & Carsten P.T. Rosenskjold & David Blake & Kevin Dowd, 2016. "Modelling Socio-Economic Differences in the Mortality of Danish Males Using a New Affluence Index," CREATES Research Papers 2016-14, Department of Economics and Business Economics, Aarhus University.
    4. Cairns, Andrew J.G., 2011. "Modelling and management of longevity risk: Approximations to survivor functions and dynamic hedging," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 438-453.
    5. Kwok, Kai Yin & Chiu, Mei Choi & Wong, Hoi Ying, 2016. "Demand for longevity securities under relative performance concerns: Stochastic differential games with cointegration," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 353-366.
    6. Liu, Yanxin & Li, Johnny Siu-Hang, 2016. "It’s all in the hidden states: A longevity hedging strategy with an explicit measure of population basis risk," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 301-319.
    7. Liu, Yanxin & Li, Johnny Siu-Hang, 2015. "The age pattern of transitory mortality jumps and its impact on the pricing of catastrophic mortality bonds," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 135-150.
    8. Ekheden, Erland & Hössjer, Ola, 2015. "Multivariate time series modeling, estimation and prediction of mortalities," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 156-171.
    9. Risk, J. & Ludkovski, M., 2016. "Statistical emulators for pricing and hedging longevity risk products," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 45-60.
    10. Clemente De Rosa & Elisa Luciano & Luca Regis, 2015. "Basis risk in static versus dynamic longevity-risk hedging," Carlo Alberto Notebooks 425, Collegio Carlo Alberto, revised Oct 2015.
    11. Lin, Tzuling & Wang, Chou-Wen & Tsai, Cary Chi-Liang, 2015. "Age-specific copula-AR-GARCH mortality models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 110-124.
    12. James Risk & Michael Ludkovski, 2015. "Statistical Emulators for Pricing and Hedging Longevity Risk Products," Papers 1508.00310, arXiv.org, revised Sep 2015.

    More about this item

    JEL classification:

    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:quantf:v:14:y:2014:i:2:p:217-235. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Chris Longhurst). General contact details of provider: http://www.tandfonline.com/RQUF20 .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.